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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2017/01/04 00:13:58 UTC
[jira] [Commented] (SPARK-16786) LDA topic distributions for new
documents in PySpark
[ https://issues.apache.org/jira/browse/SPARK-16786?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15796648#comment-15796648 ]
Joseph K. Bradley commented on SPARK-16786:
-------------------------------------------
[~supremekai] Thanks for the PR. I'm sorry about the inactivity on this. However, now that it has been added to the DataFrame-based API (in pyspark.ml), we will not be adding it to the RDD-based API. I'll close this issue.
> LDA topic distributions for new documents in PySpark
> ----------------------------------------------------
>
> Key: SPARK-16786
> URL: https://issues.apache.org/jira/browse/SPARK-16786
> Project: Spark
> Issue Type: Improvement
> Components: MLlib, PySpark
> Affects Versions: 2.0.0
> Environment: N/A
> Reporter: Jordan Beauchamp
> Priority: Minor
> Labels: patch
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> pyspark.mllib.clustering.LDAModel has no way to estimate the topic distribution for new documents. However, this functionality exists in org.apache.spark.mllib.clustering.LDAModel. This change would only require setting up the API calls. I have forked the spark repo and implemented the changes locally
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